Hi, The only pages I could find on KML_BLAS were in Chinese. Like Matti, I'd be interested to know about the license for this library. Which particular ARM chips will it run on?
Cheers, Matthew On Mon, Feb 22, 2021 at 12:15 PM ChunLin Fang <qiy...@gmail.com> wrote: > > Hi all, > Whether you're running apps on your phone or the world's fastest > supercomputer, you're most likely running ARM. Many major events have > occurred related to ARM archtecture: > > Apple may have done the most to make ARM relatively relevant in popular > culture with its new ARM-based M1 processor. > Amazon Web Services launched its Graviton2 processors based on the Arm > architecture , which promise up to 40% better performance from comparable > x86-based instances for 20% less. > Microsoft currently uses Arm-based chips from Qualcomm in some of its Surface > PCs. > Huawei unveiled a new chipset called the Kunpeng based on ARM, designed to go > into its new TaiShan servers, in a bid to boost its nascent cloud business. > > So It's obvious that ARM will become more and more popular in the > future, Since Intel MKL has provide good accelerate support for X86-based > chips, Huawei also published KML_BLAS(kunpeng math library blas) that can > make full advantage of ARM-based chips, KML_BLAS is a mathematical library > for basic linear algebra operations. it provides three levels of > high-performance vector operations: vector-vector operations, vector-matrix > operations, and matrix-matrix operations. The performance advantage is shown > in the attachment compared with OpenBlas. Can we add KML_BLAS support to > numpy? > > Cheers, > Chunlin Fang(github ID:Qiyu8) > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
